Risk is something which we all encounter in our everyday lives. For example, we risk being involved in an accident whenever we travel in a motor vehicle. Generally speaking, risk can be defined as the likelihood of some event occurring by the impact or consequences of that event; that is, risk=likelihood*impact.
A great deal of research has been undertaken in order to develop techniques for determining risk. Some of the more common techniques include: statistical analysis; forward simulations; mathematical modelling; and judgement or guessing. The problem with existing techniques for determining risk is that they do not take into account the validity of the information or process used to derive the risk. For example, where risk is determined using statistical analysis (of sampled data) the validity of the risk calculation (that is, the level of confidence a person can have in the risk calculation) will depend to some degree on the number of data samples used in the statistical analysis. Where only a few samples are taken the validity of the risk would be lower than if the risk were derived using a large number of samples.
Unfortunately, existing methods do not provide any indication as to the validity of a risk calculation. Consequently, a person using the risk calculation is unable to determine just how much confidence he/she can have in the calculated risk. This can be detrimental if, for example, a person has too much confidence in a risk calculation which is based on statistical analysis using only a few data samples (a low validity).
Existing techniques for determining risk assessment also do not give any indication as to the level of acceptability of the event occurring.